Research progress on wireless sensor networks for mechanical vibration monitoring: a CiteSpace visualization analysis approach

The application of wireless sensor networks (WSNs) in mechanical vibration monitoring is pivotal for achieving efficient monitoring within the realms of industrial automation and intelligent manufacturing, playing a significant role in the digital transformation and upgrading of China's manufacturing industry. This paper provides a comprehensive overview of the major technological advancements made by scholars and institutions globally over the past sixteen years in the domain of mechanical vibration monitoring using WSNs. Subsequently, employing CiteSpace for knowledge mapping and visualization, a multifaceted statistical analysis is conducted on over four hundred publications from both domestic and international sources. Through clustering analysis, keyword co-occurrence, and other analytical techniques, the paper delineates the multidimensional evolution of research hotspots and the dynamics of author collaboration networks over time. Building on this foundation, the paper delves into the cutting-edge trends of the field, emphasizing the critical importance of establishing efficient energy management systems and leveraging machine learning and artificial intelligence to process large-scale sensor data. These strategies are essential for optimizing system performance and propelling the development of WSNs towards miniaturization, integration, multifunctionality, systematization, and networking. The synergistic effects of these measures are anticipated to provide robust support for the intelligent upgrade of the manufacturing industry, fostering its progression towards greater efficiency and intelligence.